1. Technical Field
The present invention relates generally to methods for correlating program content and advertising and, more particularly, to a method of determining correlations and causality between media program and commercial content and consumer responsiveness which involves identifying and storing media and commercial program time occurrence and content information and consumer media reviewing actions which occur in connection with the media and commercial program time occurrence and content information, correlating that information to obtain and assign responsiveness probability values corresponding to type and intensity of consumer response for each of the media and commercial program time occurrence and content information, then applying those responsiveness probability values to a second media program to place product and service advertising at a specific time within specific content therein as determined by the responsiveness probability values.
2. Description of the Priority Art
It is well-known that certain types of television programming appeal to certain types of television viewers. For example, the types of viewers who will watch a “Matlock” rerun will be a very different demographic than those that watch the “Ultimate Fighting Championship,” and, of course, the type of advertising shown during those two shows would be quite different also to appeal to the expected viewers. This type of viewer information has been long-available and has been used for many years to direct the placement of advertising within the shows. However, this method of advertising placement does not always provide exceptional results, as there will always be elements of the programs which do not appeal to certain viewers and types of viewers, and elements of the programs which have increased appeal for certain viewers and types of viewers. Unfortunately, there are few methods by which the specific content of programs may be examined and weighted by their appeal, and those methods stop well short of the type and level of execution necessary to fully address this issue. There is therefore a need for a method of examining programs to identify specific elements therein to determine audience reaction to those specific elements.
Once those specific elements are known and the audience reaction to those elements is ascertained, it then should become theoretically possible to anticipate audience reaction to similar events in future programs. Additionally, it should be possible to examine previously aired programs and commercials to predict likely response to new advertisements or explain why certain advertising campaigns did or did not work using those same shows. Advertising and product placements may then theoretically be focused on those specific elements to increase the “bang” for the advertiser's buck, in other words, the same element occurring in the future program will likely produce the same or similar reaction and therefore the advertising best suited to appeal to the particular audience given the expected audience reaction occurring at that time in the program would be placed at that point in the program. As a corollary to this it is also probable that by using more of the same element that was seen to work previously one could yield better results than otherwise. However, at this time, not a single example is found in the prior art which addresses and solves this need.
For example, some of the more relevant prior art includes technology which attempts to categorize a viewer based on the types of shows he watches, as well as demographic information and indicated preferences. By way of example, Predictive Networks, Inc. has previously used this system for targeting Internet users and is attempting to and sought to adapt it for interactive television. The system places users at specific points in an X/Y axis, x being education, y being income. For example, an individual who visits Textbooks.com will be placed in a high education, low-income point on the graph. These events are collected over time so that advertisements can be sent to viewers whom the manufacturer feels represent the correct target audience.
Most other personalization techniques try to categorize each viewer into a given profile based on a number of preferences exhibited by the viewer. These may be collected through surveys, responses to product offers, etc. Thus, their likelihood of accepting or not accepting an advertisement is based on how they have been categorized, or how they have previously responded. This “personalized” advertising utilizes several different types of collaborative filtering, and these include such approaches as illustrated below.
Companies will track the types of programs a consumer watches. Based on the types of shows, they identify the types of advertisements the individual may want to see. For example, someone who watches sports shows often might receive an advertisement for sports apparel. This is part of the intended nature of “targeted” advertisements . . . two neighbors who are watching the same show may receive different commercials. This program data is combined with data such as demographic information concerning the consumer, or preferences indicated by the consumer through surveys and questionnaires. Each of the currently operating companies which use these approaches has a slightly different approach, but each one has a “determination engine” or “matching engine” that determines, based on this data, which groups of individuals will receive given advertisements.
Another approach to advertising on television is “enhanced” advertising, which takes an existing advertisement and enhances it with an interactive “overlay”. This is a digital graphic image placed over the existing advertisement, which usually offers the consumer a chance to buy the product, get more information about it, or enter a contest. These responses are collected and the names and addresses of the responders are sent to the manufacturer of the advertised product. However, none of the prior art specifically matches program and commercial content with consumer responses to product placements and advertising within and between the program down to time frames of only seconds, and does so using an easily applied and relatively straightforward mathematical formula.
Therefore, an object of the present invention is to provide an improved method of determining correlations and causality between media programs and commercial content and consumer responsiveness thereto.
Another object of the present invention is to provide an improved method of determining correlations and causality relationships between media program and commercial content and consumer responsiveness in which media and commercial program time occurrence and content information and consumer media actions are identified, detected and stored to provide a growing database of such information which is usable by the present invention.
Another object of the present invention is to provide an improved method of determining correlations and causality relationships between media program and commercial content and consumer responsiveness which can be used to identify likely time and content locations within media programs that selected desirable viewers will be watching the program, and then to place embedded advertising including scrolling graphics and texts and product placements in those locations to improve responsiveness to those ads.
Another object of the present invention is to provide an improved method of determining correlations and causality between media program and commercial content and consumer responsiveness which further predicts which content elements of the commercial's to use with what program content elements to gain the best response rate to the commercial, specifically, the method considers not just the content of the media program but also the content of the commercial and how that interplays with the media program.
Finally, an object of the present invention is to provide an improved method of determining correlations and causality between media program content and consumer responsiveness which is relatively simple and straightforward in design and furthermore is safe, efficient and effective in use.